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AWS Machine Learning Blog surveys year-to-date SageMaker AI inference work across fully managed endpoints and HyperPod Inference.
No defensible location · Amazon SageMaker HyperPod Inference · Amazon Web Services · AWS Machine Learning Blog · Amazon SageMaker AI · 1 sources
The open-weight model is available for coding and knowledge work, with native vision, a 1-million-token context window, and explicit prompt caching.
No defensible location · No defensible location
Amazon Bedrock · Moonshot AI · Amazon Web Services
The production-oriented runtime reclaims memory as sessions end and keeps cold starts consistent, regardless of image size or concurrency.
No defensible location · No defensible location
AgentCore runtime · Amazon Bedrock AgentCore · Amazon Web Services
A coding agent pointed at a Hugging Face model is meant to stand up a SageMaker real-time endpoint with serving, autoscaling, CloudWatch alarms, and a verified teardown path.
No defensible location · No defensible location
Amazon CloudWatch · Amazon Web Services · Hugging Face · Amazon SageMaker AI
The Kubernetes-native router uses live GPU signals to pick the best pod for each inference request and can cut first-token latency by up to 82%.
Amazon Web Services · Organization anchor
Amazon SageMaker HyperPod · Amazon SageMaker HyperPod Inference Gateway · Amazon EKS · Amazon Web Services · AWS Machine Learning Blog
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